Demystifying AdTech trends

Over the last 35 years, I’ve seen new media and adtech evolve from a fragmented ecosystem into a deeply interconnected maze of platforms, partners, data, and shifting industry trends.

What appears chaotic on the surface often reveals larger structural patterns underneath. Here’s my take on where this maze may be headed, and what the industry should prepare for before the next turn arrives.

One: The Smarter Web

The web of AdTech is still open, and in many ways, it has become far more intelligent than it was ever designed to be.

What began as a system driven largely by real-time bidding has gradually evolved into one shaped by continuous, real-time interpretation. Today, AI layers evaluate intent, context, environment, and likely outcomes at a speed and scale that no manual system could have sustained.

The shift has become more of a structural one than a technological one. Decision-making is no longer confined to transactions, but embedded across the entire user journey. But throughout all of this, the openness of the web ecosystem continues to hold.

Web publishers, apps, gaming studios, SSPs, and ad networks continue to contribute to a structure that allows broad participation and growth, and is remarkably democratic. That collective nature across partners remains one of the web’s enduring strengths.

What is becoming more visible, however, is the growing role of intelligence in shaping how value flows across this system. As these capabilities deepen, they are likely to play an increasingly central role in how the ecosystem evolves from here.

It is a shift worth observing closely as the ecosystem continues to take shape.

Two: AI-led Decisioning

AdOps used to be a lot like babysitting.

Delivery had to be monitored, budgets paced, bids adjusted, creatives rotated, often through constant manual intervention. Campaign performances depended heavily on how closely all this was being watched.

I have spent enough time in adtech to know that the anxiety was the job. It was built on attentiveness, where small, timely actions influenced outcomes. But that's changing fast.

In 2026, that layer has been quietly transforming. Optimization engines don't need to be constantly monitored by humans anymore. AI agents can read signals, understand intent, and respond in real-time across multiple variables before a human analyst has even opened their dashboard, bringing a level of continuity that manual processes could rarely sustain.

The focus is moving away from individual adjustments towards shaping ad stack structure, ensuring compliance, and defining how ad revenue is realised over time.

In this transition, smart organisations are building exactly for this shift: intelligence-led decisioning inside an ecosystem that doesn't wait around for human input to function.

Anyone building a truly autonomous, intelligent AdOps stack is building for the present. Not the future. The present.

Human-in-the-loop still matters but the job now is to monitor the autonomous ecosystem, course-correct it, and make sure it's learning the right things for the right reasons.

Three: Autonomous User Acquisition

Something has significantly changed in one of the most important aspects of AdTech and it has started to feel very different from what it used to be.

It is User Acquisition.

What felt like a reaction to performance, now feels quite proactive in nature. From what I have very closely observed, UA earlier was the ability to interpret signals after they appeared. One would just answer questions such as which audience responded, which channel delivered, which creative worked. The cycle was familiar: launch, observe, refine. It all depended on how efficiently those loops were managed.

What I see evolving, is the position of this loop itself. The decisions are being shaped before outcomes fully materialise. There are systems mapping audience behaviour, identifying lookalike patterns, estimating lifetime value, and running multiple scenarios in parallel, interestingly, often across channels that were earlier managed in isolation.

As a consequence, what has changed quietly, but meaningfully, is the role of UA teams. The emphasis again lies less on optimising individual campaigns but more on ensuring that the broader system is aligned, responsive, and able to sustain outcomes over time.

And what's the future? Well, I feel managing campaigns will always matter. But the edge going forward would be in how effectively those systems are guided.

UA has adapted and will always evolve alongside, and the maze will be an interesting one to look at!

Four: Gaming monetisation

The Gaming industry. A highly dynamic ecosystem which has emerged as a platform innovating one of the most advanced ways of thinking in AdTech. What stands out is not the scaling and engagement but the way they approach monetisation within its constraints.

Monetisation here cannot exist independently of experience; it has to be designed into it, very smartly. It is a space where engagement is continuous, attention is earned, and any friction is immediately visible. Clearly, this environment pushes studios to think about value creation in ways that feel far more integrated and seamless.

Over time, this has led to the emergence of newer monetisation approaches. Rewarded formats, in-app economies, hybrid mediation layers, and increasingly AI-led personalisation are not isolated innovations. They are part of a broader attempt to align user intent with monetisation outcomes, without disrupting the experience itself.

Ideas have begun to travel too. The influence of gaming is extending into AdTech, with frameworks around engagement, retention, and value realisation increasingly drawing from how studios approach these challenges.

In this evolving landscape, I am fascinated by AdTech organisations which have been working more closely with game studios, participating in these environments and contributing to how such monetisation models are structured and scaled.

As AdTech continues to grow, gaming is likely to remain a strong reference point.

Five: People steer, AI drives

Complexity has always demanded better tools.

The future of AdTech is not a choice between people and AI. Increasingly, I find myself looking at AI and people as complementary strengths rather than separate capabilities.

The conversation around AI has largely been about capability. I believe the more important conversation is about responsibility.

As the AdTech ecosystem has expanded, so has its complexity. More channels, more formats, more signals, and significantly more data leading to dynamic decision making, more than ever.

Managing this growing maze through human effort alone is no longer practical nor will you find the value lying there. What I find encouraging is that technology has begun to evolve alongside this complexity. We see AI fully capable of functioning with greater speed and continuity reducing the operational burden which is inevitably created by the complexities around. That, however, does not diminish the role of people. If anything, it elevates it.

I strongly believe that judgment, strategic intent, business context, and long-term thinking remain deeply human responsibilities. Technology can navigate the maze, but only and only a human can decide where the journey is to be headed.

Organisations that embrace this balance where AI is applied to navigate complexity while people continue to shape strategy, relationships, and business outcomes will thrive.

Perhaps, this is where the real opportunity lies.

Not in choosing between people and AI, but in recognising that the future of AdTech will be shaped by how smartly you choose to sync them together.

Six: Growth without Gatekeepers

Every democratically healthy ecosystem shares one characteristic: it creates opportunities for all, not just advantages for a few.

I have often felt that this has been one of the greatest strengths of the growing web. The ability to scale without a single gatekeeper, allowing everyone to interact and innovate.

One can observe every layer contributing:

*Publishers improving the quality of their inventory.

*Game studios reimagining the engagement and monetisation.

*SSPs bringing in more transparency in their supply chains.

*User acquisition teams refining their abilities to find the right audience and retain them.

Isn’t it interesting? To see everyone contributing something different individually, yet the outcomes are collective. That is perhaps the essence of a truly democratic web. It progresses because every layer and string of the web is evolving and growing the whole, rather than one party dictating the path of change.

Growth is always earned through such innovations and collaborations building better experiences. Control alone will fail to do so.

At smart organisations, I see people building with this philosophy in mind. Publishers and studios make better decisions while preserving the openness that allows the broader ecosystem to thrive. As the ecosystem evolves with advanced technology, preserving this balance will become more important.

Seven: Self-driving Engines

Every story has a final chapter.

While I look forward to coming back to you with new learnings in different formats, here is a final take on “AdTech: A maze, not just a puzzle”.

When I entered digital media, we knew the ecosystem would become more intricate, more complex, but would it evolve to this extent, maybe not.

If we look back in time, success often came from understanding a few metrics and making thoughtful adjustments. Banner placements, campaign reports, and creative testing defined much of the conversation. It was a period of discovery, where every improvement taught the industry something new.

Since then, much water has flown down the digital river. Every advancement adds a new layer to the web. New formats have emerged. User experiences have become richer. Data has mushroomed. All resulting in changing expectations and the maze expanding itself, quietly, relentlessly.

Looking back, I realise that what is even more surprising is our growing ability to navigate this maze. Today, intelligent systems can interpret signals, optimise pricing, predict yield, and respond to changing user behaviour with remarkable continuity. Yet, behind every meaningful outcome one can see a human mind deciding what success should ultimately look like.

This is the balance which is becoming visible to me, in organisations like UndrAds. Their automation is helping publishers deal with complexity at scale, while people continue to define strategy, priorities, and long-term direction.

To my fellow maze navigators, complexity is not always an obstacle, mostly it is a source of opportunity. Well, you know what the irony is? The maze somehow has never been this navigable.

Thank you, folks, for walking through this maze with me. Until we meet again.